IntroductionKnee osteoarthritis is a very common chronic degenerative disease that could impose significant costs to the health system. Although osteoarthritis can affect all joints, knee osteoarthritis is the most common type among adolescents. Non-surgical treatments include corticosteroids injection, hyaluronic acid, and platelet-rich plasma. The aim of this study was to investigate the efficiency of platelet-rich plasma versus hyaluronic acid for the treatment of knee osteoarthritis.MethodsPubmed, Cochran library, Scopus and Ovid databases were investigated to identify related studies from 2000 through August 2015. To study the efficiency, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) outcome using the Standard Mean Difference (SMD) index was calculated using a random model and a confidence interval of 95%. In addition, sensitivity and cumulative analysis were conducted. The data were analyzed using RevMan 5.3.5 and Stata 12 software.ResultsSeven studies with 722 subjects (364 participants in PRP and 358 participants in the HA group) were analyzed. The WOMAC PRP compared to HA, SMD = −0.75 (95% CI: −1.33 to −0.18, I2 = 92.6%) in treatment of knee osteoarthritis was statistically significant and PRP was more effective.ConclusionThe results of this meta-analysis two years after PRP injection showed the efficacy of PRP versus HA. However, further studies are required to determine the longer-term effects.

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The non-preventable ever-increasing rate of wind power generation in market-based power systems faces the operators with challenging situations for making optimal decisions. So, it is essential to equip the operators with applicable control strategies and further corresponding control facilities. Moreover, the high-priority of cheap wind power utilisation increases the probability of transmission lines congestion. Therefore, different solutions such as transmission switching (TS) and demand response (DR) programs have been recently introduced to manage the intermittent wind power generations. Accordingly, this study addresses the social welfare maximisation problem with coordinated control of TS and DR facilities to handle the regarding uncertainties using yet another linear matrix inequality parser (YALMIP). In fact, rapid algorithm and powerful employed solvers as well as simplicity of use, make YALMIP a practical modelling and optimisation toolbox. In this respect, the MOSEK solver is preferred by YALMIP to solve the proposed mixed integer linear programming problem. In addition, wind power uncertainty is modelled using the discrete-time Markov chain approach and optimisations are performed on the 8-bus and the large-scale IEEE 118-bus test systems. Results show that the proposed control strategy is highly capable of maximising social welfare by determining the optimal control commands in a real-time manner. P transition probability matrix

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